Methods for estimating photosynthetic characteristics in plant canopies and systems and apparatus related thereto

ABSTRACT

Methods of determining and characterizing photosynthesis in plant parts of one or more plants includes capturing a plurality of images of the plant parts of the one or more plants with a sensor are provided. Fluorescence of the plant parts of the one or more plants can be measured by storing a sensor image of observed fluorescence. Light absorbed by the plant parts of the one or more plants can be estimated by observing red and/or infrared reflectance of the plant parts. A characteristic of photosynthesis such as linear electron flow in plant parts of the one or more plants can be derived using the measured fluorescence of the plant parts, the reflectance and the light absorbed by the plant parts, and/or the three-dimensional model comprising the plant parts of the one or more plants. Related apparatus and systems are also provided.

This application claims priority from U.S. Provisional Application No.61/154,405, filed on Apr. 29, 2015, which application is herebyincorporated by reference in its entirety.

STATEMENT OF GOVERNMENT RIGHTS

This invention was made with government support under DE-AR0000202awarded by the U.S. Department of Energy. The government has certainrights in the invention.

BACKGROUND

Photosynthesis is a complex plant process that can be potentiallydangerous to the plant under many circumstances. For example, energycaptured in the form of photons can exceed the rate at which the energycan be used, resulting in reactive oxygen species (ROS) production andcell damage. Many mechanisms have evolved in plants to cope with thischallenge, including some that are fast responding, such as photoprotection via the qE response, and others that are slower responding,such as the induction of genes encoding proteins that can detoxify ROS.

It is unknown how these different mechanisms are integrated and thedegree to which given mechanisms take precedence under specificenvironmental conditions. For example, the same mechanisms may beactivated in the same series when plants at low temperature aresubjected to a change in light intensity, as those that occur whenplants that are experiencing drought also experience a change in lightintensity. Therefore, understanding how real-time, dynamicallyfluctuating systems affect plant status (e.g., photosyntheticproductivity, efficiency, growth, and the like) are useful for improvinga plant's response to the environmental conditions or cues (e.g.,abiotic, biotic, and the like).

SUMMARY

Systems and methods for photosynthetic transfer rate estimation incomplex plant canopies are provided. In one embodiment, a method ofcharacterizing photosynthesis in one or more plants in isolation and incomplex canopies is provided, including capturing a plurality of imagesof the one or more plants with a sensor, and generating athree-dimensional (3D) model comprising the plant parts of the one ormore plants from the plurality of images. In one embodiment, the sensoris a camera. In another embodiment, fluorescence of the plant parts ofthe one or more plants is measured, and a characteristic ofphotosynthesis of the one or more plants is derived using the measuredfluorescence of the plant parts of the one or more plants and the 3Dmodel comprising the plant parts of the one or more plants.

In another embodiment, fluorescence of the plant parts of the one ormore plants is measured by storing a camera image of observedfluorescence and/or light of certain wavelengths that is reflected bythe plant parts of the one or more plants is estimated by observing redand/or infrared reflectance of the plant leaves. The characteristic ofphotosynthesis of the one or more plants is derived using the measuredfluorescence of the plant parts, the light absorbed by the plant parts,and the three-dimensional model comprising the plant parts of the one ormore plants.

In another embodiment, the three-dimensional model further comprises oneor more geometric parameters, comprising at least one of light positionrelative to the one or more plants, sensor position relative to the oneor more plants, and light position relative to sensor position. In oneembodiment, position of the sensor relative to the one or more plants isdetermined by time-of-flight imaging (to indicate depth).

In another embodiment, the depth information is obtained by comparingthe fluorescence images with infrared reflectance images.

In a further embodiment, two or more images of the plant taken fromdifferent, known locations can be analyzed to obtain depth information.

In various embodiments, images are analyzed to provide estimates of thelight absorbed by the leaves at different levels of the canopy, togetherwith estimates of their quantum efficiencies of photosynthesis, whichtogether can be used to estimate photosynthetic processes.

In a further embodiment, the total photosynthesis can be estimated fromthe images by considering a statistical model of the distribution ofleaves at different canopy levels wherein the leaves higher in thecanopy can shade leaves lower in the canopy effectively changing thelight intensity and also wherein leaves or parts of leaves are obscuredfrom view be leaves higher in the canopy.

Various embodiments described herein provide for more effectivecharacterization of photosynthetic efficiency of plants, enablingresearchers to distinguish and cultivate phenotypes havingcharacteristics which improve plant growth, such as improving cropyield. Related apparatus and systems are also disclosed.

BRIEF DESCRIPTION OF THE FIGURES

The patent or application file contains at least one drawing executed incolor. Copies of this patent or patent application publication withcolor drawing(s) will be provided by the Office upon request and paymentof the necessary fee.

FIG. 1A shows a three-dimensional (3D) photosynthesis modeling systemaccording to an embodiment.

FIG. 1B shows a perspective view of a 3D photosynthesis modeling systemaccording to an embodiment.

FIG. 1C shows a perspective view of a lighting system and a tray forplacing plants in a 3D photosynthesis modeling system according to anembodiment.

FIG. 1D shows a bottom detailed view of a lighting system in a 3Dphotosynthesis modeling system according to an embodiment.

FIG. 1E shows a side view of a lighting system with an unmounted sensorand a plant tray in a 3D photosynthesis modeling system according to anembodiment.

FIG. 1F shows a detailed bottom view of a lighting system and componentsof a climate control system in a 3D photosynthesis modeling systemaccording to an embodiment.

FIG. 1G shows a simplified schematic illustration of a camera in a 3Dphotosynthesis modeling system according to an embodiment.

FIGS. 2A-2K are schematic diagrams showing exemplary light sources andcamera configurations for obtaining 3D photosynthesis data using a 3Dphotosynthesis modeling system according to an embodiment.

FIG. 3 is a flowchart illustrating a method of estimating efficiency ofphotosynthesis in a plant canopy according to an embodiment.

FIGS. 4A-4F are false-color images (with black background removed forsimplicity) showing Phi2 of a plant (4A), IR-reflectance of the plant(4B), Phi2×reflectance (4C); Phi2×light (4D), reflectance×light (4E) andPhi2×reflectance×light (4F) according to an embodiment.

FIGS. 4A′-4F′ are schematic representations of the images in FIGS. 4A-4Faccording to an embodiment.

FIGS. 5A-5D show the sequence of steps used to obtain a 3Dphotosynthesis leaf model according to an embodiment.

FIGS. 5A′-5D′ are schematic representations of the images in FIGS. 5A-5Daccording to an embodiment.

FIG. 6 is a flowchart of a method of estimating the photosyntheticefficiency of plants according to an embodiment.

FIG. 7 is a computerized photosynthesis modeling system according to anembodiment.

FIGS. 8A-8C are false-color images (with black background removed forsimplicity) of a processed relative Phi-2 (LEF) image (FIG. 8A),IR-Reflectance image normalized to peak pixel value (FIG. 8B) and animage of the Phi-2 (LEF) image multiplied by the IR-Reflectance image(FIG. 8C) according to an embodiment.

FIGS. 8A′-8C′ are schematic representations of the images of FIGS.8A-8C, respectively, according to an embodiment.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings that form a part hereof and in which are shown, byway of illustration, specific embodiments in which the invention may bepracticed. These embodiments are described in sufficient detail toenable those skilled in the art to practice the invention. Otherembodiments may be utilized, and structural, logical, mechanical,electrical, and other changes may be made. Features or limitations ofvarious embodiments described herein do not limit other embodiments, andany reference to the elements, operation, and application of theembodiments serve only to define these illustrative embodiments.

Features or elements shown in various embodiments described herein canbe combined in ways other than shown and described in the variousembodiments, and any such combinations is explicitly contemplated to bewithin the scope of the embodiments presented here. The followingdetailed description does not, therefore, limit the scope of what isclaimed.

Various terms are defined herein. The definitions provided below areinclusive and not limiting, and the terms as used herein have a scopeincluding at least the definitions provided below.

The term “plant” as used herein comprises any multicellular eukaryote ofthe kingdom Plantae. It includes green plants having cell walls withcellulose that characteristically obtain most of their energy fromsunlight via photosynthesis using chloroplasts contain chlorophyll.

The term “photosynthesis” as used herein refers to any mechanism used byplants to convert light energy into chemical energy that can be releasedto fuel the plant. Photosynthesis includes, in a more detailed example,absorption of energy from light in proteins called reaction centers thatcontain green chlorophyll pigments.

The term “phototrophic organisms” as used herein refers to an organismthat obtains energy from sunlight for the synthesis of organic compoundsand include plants, algae and cyanobacteria.

The term “image” as used herein refers to any representation of anobject in one or more dimensions, including one-dimensional,two-dimensional, three-dimensional, or greater-dimensionalrepresentations of visible, infrared, ultrasonic, or other capturedinformation representing the position of objects being imaged.

The term “sensor” or “imager” as used herein refers to any device, suchas a camera or silicon sensory array, configured to capture or record animage or series of images of an object, including in one, two, three ormore dimensions. The imagers and sensors can be modified by appropriateselection of sensor filters and light filters to capture light atdifferent wavelengths (colors) to measure different properties of theplants.

The term “camera” as used herein refers to a sensor having aphotosensitive surface that records images through a lens.

The term “silicon sensory array” as used herein refers to an imagingdevice that uses a light-sensitive silicon-based semiconductor array totransfer photonic/image information into electrical information that canbe digitized for computer manipulation.

The term “sensor array” as used herein refers to any series of imagingsensors arranged and coordinated in an array to capture images thatreflect different properties or at different angles or perspectives.

The term “model” as used herein refers to a representation, whethercomplete or not, of an object or a process. A three-dimensional model asdescribed herein contains at least some information in three physicaldimensions, but need not comprise a complete three-dimensionalrepresentation of an object (such as representing only the top surfaceof a leaf or plant in three dimensions).

The term “plant parts” as used herein refers to one or more organs orregions of a plant such as leaves and flowers having plant cells andable to carry out photosynthesis.

The terms “leaf” and “leaves” as used herein refer to, respectively, oneor more organs of a vascular plant that are the principal lateralappendage of the stem. Leaves further include plant cells havingchloroplasts that contain chlorophyll, which is used to convert lightenergy into chemical energy. In some plants such as green algae, algaecells having chloroplasts that contain chlorophyll for purposes ofphotosynthesis perform this function, and are considered leaves forpurposes of this application.

The term “foliage” as used herein refers to the leaves of a plant orplants, collectively.

The term “canopy” as used herein refers to the aboveground portion of aplant or plants formed by the collection of the individual leaves of theplant or plants. In some embodiments, the canopy can include all of theleaves of the plant or plants. In some embodiments, e.g., trees, thecanopy may include an upper portion of the foliage of the plant orplants.

The term “light” as used herein refers to electromagnetic radiation inor near the visible portion of the electromagnetic spectrum from about300 nm to about 1000 nm, including visible light, ultraviolet light, andnear infrared light. The terms “light” and “lights” further compriserespectively one or more devices or apparatus configured to emit light,such as visible, infrared, or ultraviolet light.

The term “ultraviolet light” as used herein refers to electromagneticradiation having a wavelength shorter than but near the visible portionof the electromagnetic spectrum.

The term “infrared light” as used herein refers to electromagneticradiation having a wavelength longer than but near the visible portionof the electromagnetic spectrum.

The term “actinic light” as used herein refers to light that willstimulate photosynthesis in light-sensitive plants.

The term “light intensity” as used herein refers to the amount of lightpower over a given area.

The term “Photosynthetically Active Radiation” (PAR) as used hereinrefers to the light intensity that is effective at activatingphotosynthesis, typically from about 400 to about 700 nm. PAR isexpressed in units or μmoles photons m⁻²s⁻¹.

The term “Phi-2” as used herein refers to the quantum yield ofphotochemistry (or LEF) at photosystem II.

The term “light quality” as used herein refers to the spectralcomposition of light that is effective in producing photosynthesis andthe support of plant functions.

The term “fluorescence” as used herein refers to the emission of lightfrom material that has absorbed light or other radiation. Itspecifically includes absorption of sunlight or other actinic ormeasuring probe light by plants, and emission of energy from theabsorbed light as light.

The term “instrument” as used herein refers to any device operable tomeasure or record a measurable physical characteristic, such as light,temperature, time, or other characteristic.

The term “mapping” as used herein refers to application of one set ofinformation to associated elements of another set of information, suchas mapping observed plant reflectance to a three-dimensional model of aleaf or leaves.

The term “multiplying images” as used herein refers to multiplying theintensity values stored in each pixel of one image by the correspondingpixel intensity value of another image.

The term “time of flight” as used herein refers to the time required forincident light to reach the plant part or leaf. It could also relate thetime required for emitted light to reach the sensor (e.g., camera) fromthe plant part or leaf. The “time of flight” for light is approximatelyequal to the speed of light multiplied by twice the distance from thelight source to the camera or detector.

The term “linear electron flow” (LEF) as used herein refers to anelectron flow path in photosynthesis resulting from light striking alight harvesting complex in a plant, resulting in the production of ATP,NADPH, and oxygen.

It is known that rapid fluctuations in certain environmental conditionscan trigger action of certain protective mechanisms that are notrequired when the environmental condition is held constant. Plants andother organisms have evolved to cope with unpredictable, dynamicallyfluctuating environments or conditions, yet study or evaluation of theseorganisms is conducted largely under constant (laboratory) conditions.While such steady-state observations are very valuable, they areunlikely to detect novel biochemical and regulatory mechanisms that havevaluable roles in nature. For example, disrupting key photosyntheticresponses often have little effect on growth or photosynthesis in thelaboratory, but are strongly deleterious in the field.

Understanding photosynthetic activity in plants enables cropproductivity to be increased, such as by increasing photosynthesis underenvironmental stresses or other changing conditions. Some estimatessuggest that up to 70% of plant productivity is lost due toenvironmental conditions that impact photosynthesis, and understandinghow photosynthetic networks respond to changes in environmentalconditions has the potential to lead to design of plants with increasedphotosynthetic efficiency.

To increase understanding of photosynthetic activity in plants underenvironmental stresses, efforts have been made to determine mechanismsof photosynthetic acclimation to environmental factors. However, theseefforts are based on growing plants in highly controlled growth chambersunder a given condition, or exposing plants to a change in a singlecondition, and then following the effects over time on thephotosynthetic parameter under study. While this experimental design isuseful, such a strategy is unlikely to detect the specific biochemicaland regulatory mechanisms that are relevant in nature, such asdisruptions in key photosynthetic responses. Such mechanisms typicallyhave little effect on growth or photosynthesis in the lab, but can bestrongly deleterious in the field.

Plants can accommodate a wide range of conditions provided they areconstant or occur with regularity so that acclimation processes canadjust gene expression, biochemical activities, growth and morphology,etc. Severe stress occurs when the extent of environmental conditionsexceeds the physical limits of the organism or when fluctuations occurmore rapidly than acclimation responses. Photosynthesis is particularlysensitive to fluctuating environmental conditions. The environmentalconditions most directly relevant to photosynthesis, such as lightintensity, light quality, temperature, CO₂ levels, etc., are the mostdynamic in nature (i.e., they change rapidly and over a wide range). Ifnot well regulated, photosynthesis can generate toxic side reactions,especially under fluctuating environments. To prevent this photodamage,the light reactions of photosynthesis are highly regulated. Plantsrespond to rapid (seconds to minutes) changes in environmentalconditions by activating a series of biochemical processes that controllight capture, including non-photochemical quenching via the qEmechanism, antenna state transitions, regulation of the thylakoid protonmotive force (pmf) via the activity of the chloroplast ATP synthase andion gradients, and regulation of electron transfer at the cytochrome b6fcomplex.

Fluctuating conditions can be markedly more harmful than static orslowly appearing conditions for several reasons. Slow onset ofconditions can be dealt with using the entire suite of plant regulatoryresponses. In contrast, rapidly appearing conditions must be dealt withusing existing biochemical/biophysical regulatory processes. Individualplant regulatory responses are regulated by different phenomena andrespond with different dynamics so that while gradually imposed stressmay be compensated, rapid fluctuations may not.

Many genes have clear functions, as demonstrated by losses of functionwhen they are mutated or suppressed. However, lack of knowledge of plantperformance under more diverse conditions means that the functions ofmany genes are obscure; modifying their expression results in little ofno apparent phenotypes under laboratory conditions.

Photosynthesis can be modeled and observed using chlorophyllfluorescence imaging to obtain estimates of photosynthetic efficiency,but effectiveness of such methods often relies upon the plants beingstudied having a relatively simple plant structure that can be easilyimaged for fluorescence. It is difficult to apply such methods to manyimportant crop or biofuel plants having complex plant structuresconsisting of multiple leaf layers, making study and characterization ofdevelopmental differences and photosynthetic capacities difficult. Inaddition, plants grow in complex canopies, e.g., differential heightsand overlap of leaves within the canopies, which preclude the estimationof photosynthesis using simple imaging approaches. Additionally, thebiochemical and physiological properties of leaves at different levelsof the canopies can be distinct, preventing the application of modelingthat does not directly measure or consider these differences.

Essentially, complex canopies are highly dynamic and change theirstructure over a range of time scales, from wind-induced movement on theorder of seconds, to changes in light penetration with the position ofthe sun on the order of hours, to alterations in plant structure andmorphology, as well as changes caused by exposure to precipitation.Methods that rely on simple 3D modeling approaches such as modeling byusing stereoscope images may not be applicable and/or accurate forcomplex canopies with leaves that are moved by wind and/or precipitationor which have other plant-induced movements. Other 3D imaging methodswhich require lengthy image acquisition may also not be feasible incomplex canopies.

With respect to specific types of imaging, it is known that linearelectron flow (LEF), which is proportional to Phi-2 multiplied by theincident (absorbed) PAR, can be determined by multiplying the Phi-2image by a scalar PAR value measured at some location near the plantcanopy. However, this scalar PAR value may not be representative of thehighly variable PAR values localized to specific areas of a plantcanopy. LEF images can be conventionally represented by multiplying thePhi-2 image by a scalar PAR value and an assumed absorbance. However,this method can be inaccurate, as it does not follow the variation inlight intensity throughout the plant canopy.

Because controlled environment chambers and greenhouses do not reproducekey environmental conditions important for plant responses, researchconducted in these devices can miss key biochemical and genetic targetsfor crop improvement and can also provide misleading indications ofpotential field performance. Various embodiments described herein remedythis deficiency by better capturing the effects of key environmentaldynamics on plant performance using new approaches to phenometric study.

What is needed, therefore, is an approach that characterizes phenotypesunder more substantially natural fluctuating environmental conditions incomplex plant canopies as are typically found in the field. The systemsand methods provided herein allow for measuring of phenotypes undersubstantially natural environmental conditions by estimating aphotosynthetic transfer rate in complex plant canopies, such as by usingthree-dimensional models of plant canopies. In the various embodimentsdescribed herein, a more accurate LEF measurement may be obtained byusing localized PAR values determined through imaging. TheIR-Reflectance value can be representative of localized light intensity.(See Example). In various embodiments, this improved accuracy can befurther refined by including the localized absorbance values for theabsorption of red measurement light.

The various embodiments described herein provide for both a 3Dphotosynthesis modeling method (“3D method”) (which combines multiplyingand geometric modeling, as shown for example, in FIGS. 3 and 4) and a“multiplying method” which determines information (e.g., photosyntheticcharacteristics) on plant canopies by multiplying images obtained usinglights and cameras at different angles, as described herein, to provide“3D-type” information, as shown in the Example and in FIGS. 8A-8C. This“3D-type” information includes information related to lower plant parts,such as lower leaf layers and/or leaves which may be tilted away fromthe light, and so on. It is to be understood that the various equipmentand apparatus described herein and shown in FIGS. 1A-1G as being usefulfor the 3D modeling method, and the various configurations of lightsources and camera configurations described herein and shown in FIGS.2A-2K, as being useful for the 3D modeling method, can also be used forthe multiplying method.

FIG. 1A shows one embodiment of a 3D photosynthesis modeling system(hereinafter “photosystem”) 100 for estimating photosynthetic transferrate in complex plant canopies. In one embodiment, the photosystem 100is a three-dimensional (3D) modeling system referred to herein as a“3D-Dynamic Environmental Phenotype Imager (3D-DEPI)” system. In thisembodiment, the photosystem 100 includes a chamber 102 in which aplurality of plants 122 can be measured with a variety of associatedequipment contained therein. In this embodiment, the plants 122 arearranged side-by-side as they might exist in nature or in a crop plantenvironment, such that their foliage combines to form a canopy at thetop of the plants, although other configurations can be used, includingexpansion to smaller and much larger scales. Associated equipmentincludes, but is not limited to, climate control equipment, such asheating and cooling apparatus 106, and humidity control apparatus 120.In a further embodiment, the gas content of the chamber 102 isregulated, such as by controlling the amount of carbon dioxide, oxygenand/or other gasses by regulating, for example, gas tanks 108 and 110 inthe chamber 102.

FIGS. 1B through 1G show additional embodiments and/or detailed featuresof photosystem 100. In the embodiment shown in FIG. 1B, the photosystem100 includes chamber 102 sized to house the plant or plants 122. Thephotosystem 100 can include housing 140 configured to accommodate someand/or all of the components of photosystem 100. In the embodiment shownin FIG. 1B, the photosystem 100 further includes tray 134. Plants 122may be placed on the floor of chamber 102 and/or tray 134. Tray 134 maybe removable from chamber 102.

A variety of materials may be used as the housing 140 for photosystem100. In various embodiments, housing 140 may be polymer based materials,metals such as aluminum, steel and the like. Other materials are alsocontemplated for the housing and are within the scope of thisdisclosure. In one embodiment, photosystem 100 may also be a framedstructure wherein chamber 102 is not enclosed but is open or partiallyopen on the sides and/or the top. Photosystem 100 can be made from anymaterial that allows isolation of the grow area from the outsideenvironment. In one embodiment, the photosystem can be scaled from about1 cubic meter to about 3 cubic meters. Photosystems smaller and largerthan these volumes are also within the scope of this description.

As shown in FIGS. 1A-1G, photosystem 100 can further include lightingsystem 124 comprising one or more lighting arrays 126. As shown in FIG.1C, in one embodiment, lighting system 124 includes frame 128 configuredto accommodate one or more lighting arrays 126. One or more lightingarrays 126 may be mounted onto frame 128. Each of the lighting arrays126 can include one or more rows of lights with each row including oneor more lights 112. In one embodiment, lighting system 124 and lightingarrays 126 are configured as shown in FIGS. 1C-1F. In one embodiment asshown in FIG. 1D, lighting array 126 is shown as having two outer rowsof lights 112 and a center row of lights 113, although the variousembodiments are not so limited. In one embodiment, center row of lights113 may be an auxiliary set of lights. Each of the lighting arrays 126can have the same combination of lights 112 and/or 113, e.g., actinic,infrared, etc. or a different combination of lights 112 and 113. In oneembodiment, the auxiliary set of lights 113 may have a lower intensitythan the outer row of lights 112. In a further embodiment, the auxiliarylights 113 may have a lower intensity and can be the measurement lightsource and the outer row of lights 112 can be the actinic light source.

In one embodiment, as shown in FIG. 1D, lighting arrays 126 can includeconnectors 130 which connect lighting system 124 to heating and/orcooling apparatus 106 by hoses or tubes.

In various embodiments, lighting arrays 126 of lighting system 124 caninclude lights 112, which can, in one embodiment, include light-emittingdiodes (LEDs) such as high color-rendering index LEDs that provide abroad spectrum of light. In the embodiment shown in FIG. 1D, lights 112can include the actinic lighting source, the infrared lighting sourceand/or the measurement lighting source. In one embodiment, the highcolor-rendering index LEDs are from Yuji International. Lighting arrays126 can also include auxiliary lights 113, which can serve as auxiliarylight sources, and, in one embodiment, include an LED array of lightswith different wavelength profiles. Lights 112 and 113 may be of same ordifferent sources, emit same or different light intensities and havesame or different light qualities to serve different roles in plantillumination or measurement.

Lights 113 can include actinic light sources, infrared light sourcesand/or measurement light sources. In various embodiments, auxiliarylights 113 can include a plurality of lights, each having a differentwavelength profile, such as a red or infrared output, such that thedifferent lights can be selectively controlled to create various lightconditions within the chamber 102.

In various embodiments, lights or illumination sources are capable ofproviding light that simulates sunlight (or the full solar spectrum) andthat can be altered. In one embodiment, the light provides actinicillumination. Such actinic light may include light that may activate thephotosynthetic apparatus as well as biological light sensors, such asphytochromes, cryptocromes and green light receptors that affect thegrowth, development and other behaviors (e.g., chloroplast movements) ofthe organisms.

Light sources may include, in various embodiments, halogen lamps, one ormore light emitting diodes (LEDs), lasers, specially designed xenonlamps and the like, and a combinations thereof.

Compared to fluorescent and incandescent lighting, LEDs with appropriateoptics can deliver higher light intensities at greater distances withmore precise control over light intensity, and more rapid and preciseswitching (on and off). This level of control allows capturing afluorescence image generated from a pulsed light of fixed duration andintensity during a brief interval in which actinic illumination isswitched off or shuttered.

In one embodiment, the LED illumination system can include a lightsource that comprises one or more LED or Organic Light-Emitting Diode(OLED), where the LED(s) can emit light at different wavelengths. In oneembodiment, white LED lighting may be used as the actinic light.Spectrally, these lights more closely resemble natural lightingconditions that are used for growing plants, as compared to individualor combinations of LEDs of discrete wavelengths. Exemplary white LEDscan provide a wavelength from: about 380 nm to about 750 nm or about 420nm to about 730 nm, including any range or value therebetween. WhiteLEDs with a colored temperature of from about 5000K to about 7000K,including any range or value therebetween, may also be used. In oneembodiment, commercially available white LEDs are used, such asBridgelux 50 watt white LED arrays or Cree 10 watt white LEDs. In otherembodiments, light approximating solar emission can be simulated bycombining light from a series of LEDs with a range of emissionwavelength that span the solar spectrum. In one embodiment, the overallspectrum may be tuned by changing the emission from each type of LED byadjusting its electrical current.

A measuring light source (e.g., probe or pulsed light) used to excitechlorophyll fluorescence may include white or monochromatic light suchas a red, blue or green LEDs or any light within the visible range. Suchmeasuring light may be provided by LEDs (e.g., red LEDs, blue LEDs orgreen LEDs). In addition, near UV and UV LEDs can be incorporated assupplemental illumination to allow the activating light to better matchthe solar spectrum and to probe fluorescent pigments in the plant partsor to induce UV-sensitive processes.

In one embodiment, light sources may further include compound parabolicconcentrators to collimate the light. Such a configuration may, in someembodiments, better simulate sunlight and allow for higher lightintensities to be reached at greater distances. In various embodiments,the light source for growth may be configured or adapted to providecontinuous white light intensities at or in excess of full sunlight upto any suitable amount (e.g., fluencies from about 2,500μ moles photonsm⁻²s⁻¹ up to about 10-fold (10×) higher than full sunlight, i.e., about25,000μ moles photons m⁻²s⁻¹), such as about 2×, about 3×, about 4×,about 5×, about 6×, about 7×, about 8×, about 9× higher than fullsunlight, further including any range or value therebetween. In variousembodiments, photosynthetic measurements may be made at any suitabledistance between the light(s) and the plants, such as from: about 0.5 toabout 3 meters, about 1 meter to about 2 meters, about 0.5 meters toabout 1.5 meters, or at least 1.5 meters, at least 2 meters, at least2.5 meters, or, at least 3 meters, further including any range or valuetherebetween. In other embodiments, the distances may be greater orsmaller, depending on the size of the plant chamber, the configurationof the camera(s), light(s) and plant(s), and so forth.

In one embodiment, power supplies that support light intensities fromabout 2400 to about 3000μ moles photons m⁻²s⁻¹, such as in excess ofabout 2,500μ moles photons m⁻²s⁻¹, up to any suitable amount such as upto 10× higher than full sunlight, including all the ranges and valuesdiscussed above, are used, although the embodiments are not so limited.In various embodiments, power to the LEDs may be provided by anysuitable source, including DC power supplies, conventional batteries,and the like.

Light intensity and light quality may also be adjusted. In oneembodiment, light may be adjusted by regulating the electrical currentpassing through an LED. This may be accomplished by computer control viaan electrical circuit that regulates the conductive status of atransistor or similar device. In one embodiment, a programmable highspeed timing card or similar device including a preconfigured FullyProgrammable Gate Array (FPGA) or microcontroller can be used to sendsignals for setting intensity by a control circuit (such as a currentlimited feedback control circuit) and for rapidly switching actiniclight off and on by a rapid gating circuit (such as a rapid switchcircuit using MOSFETs and MOSFET controllers).

In one embodiment, light quality can be controlled by supplementalillumination with separate LED arrays of various colors, includingultraviolet, visible and near infrared light. In one embodiment, thelight quality (the distribution of light intensity across the solarelectromagnetic spectrum near the visible), can be adjusted to matchthat of solar irradiation or that in different environments. In oneembodiment, the light quality may be adjusted to match that measured ona cloudless day, deep within a plant canopy or in commercialgreenhouses.

Depending on the environmental condition or the parameter to beevaluated, appropriate sensors may be used. In one embodiment, if lightis the environmental cue, various sensors can be used. Exemplary sensorsinclude, but are not limited to, cameras, such as video cameras, hightime resolution computer controlled video cameras, cameras with chargecoupled devices (CCD), complementary metaloxide semiconductor (CMOS)cameras, and the like. In one embodiment, the sensor comprises one ormore cameras. These cameras may be further equipped with optical filtersto collect chlorophyll fluorescence images. In one embodiment, thecameras may include filters for far red or near infrared (about 630 nmto about 950 nm) where chlorophyll fluorescence occurs. The sensors caninclude one or more sensors and may be arranged in any configuration toallow for imaging any area configuration. For simplicity, the term“sensor” is hereinafter used interchangeably with the term “camera,”although it is understood that other types of sensors, other than acamera, may be used.

As shown in FIG. 1A, one or more cameras 114 are also provided as partof photosystem 100, which, in various embodiments, are operable to imagevisible light, infrared or thermal light, ultraviolet light, or otherspectra of light. In one embodiment, one or more cameras 114 shown inFIG. 1G include camera body 114 a, lens 114 b and one or more filters114 c. In various embodiments, one or more cameras 114 haveinterchangeable filters 114 c that enable detection of different lightspectra, while in other embodiments the image captured by the camerascan be filtered to image only the wavelengths of interest. In oneembodiment, camera 114 is a single camera that is operable to changeposition within or outside of housing 140. In other embodiments,photosystem 100 comprises a number of cameras 114 used simultaneously asshown in FIG. 1A.

In addition to the aforementioned light(s) 112, camera(s) 114, heatingand cooling apparatus 106, humidity control apparatus 120, gasregulating equipment to monitor and regulate gasses in gas tanks 108 and110, respectively, can be used via a computerized system 116, such asunder the command of a user 118. In one embodiment, as shown in FIG. 1B,computerized system 116 can include system 116 a for cooling electronicsand lighting assembly 124, desktop computer 116 b for running program tocontrol the photosystem 100 and to collect and store data, andcontroller 116 c for controlling one or more lights 112 and one or morecameras 114. Other computer components may be used as needed formodulating the components of the photosystem.

In a further embodiment, one or more of the cameras 114 includetime-of-flight capability, such as observing or measuring time-of-flightof a laser or other projected signal toward the plant canopy, such thata characterization of distance from the cameras 114 to the leaves 104 ofplants 122 forming the plant canopy can be measured and/or imaged.

In various embodiments, the sensor 114 as shown in FIG. 1C may beincorporated into lighting system 124. In one embodiment, integration ofmultiple cameras into the photosystem 100 allows substantiallysimultaneous imaging of the entire growing area, thus minimizing datacollection time and external stress on plant groups by eliminating theneed to move the plants individually from the enclosure to an imagingdevice.

In one embodiment, photosystem 100 may also be equipped with a sensor114 wherein the sensor 114 can be used for thermal imaging (e.g., forterahertz (THz) imaging) and spectroscopy. In such embodiments,non-ionizing radiation is provided to the plants 122, or, morespecifically, to one or more plant parts, such as leaves, flowers and/orfruits to non-invasively monitor the plant 122. In various embodiments,using THz wavelengths, which are sufficiently short, allow for imagingof e.g., vein and stems. The THz non-ionizing radiation may also be ableto be absorbed by water, making it a useful tool to detect plantmoisture content in parts of a plant 122, such as in a leaf 104. THzimaging may be used alone or in combination with chlorophyll florescenceimaging or other parameters being studied. In such cases, therelationship of water movement and photosynthesis may be evaluated.

In operation, user 118 places one or more plants 122 in chamber 102and/or on tray 134, and adjusts the environment within the chamber 102to selected conditions, such as by adjusting lights 112, cameras 114,heating and cooling apparatus 106, humidity apparatus 120, and gas tanks106 and 108, to provide a suitable mixture of gasses, such as carbondioxide 108 and oxygen 110, respectively.

In one embodiment, light sources 112 provide various wavelengths orcombination of wavelengths. The light source may also, in oneembodiment, be configured to allow dynamic control over light intensity,duration and quality. In other words, in one embodiment, the lightsource reproduces natural light intensity fluctuations that occur underfield conditions. To this end, the system may, in various embodiments,be adapted to accept any number of lights, in any suitable combination,allowing the light spectral quality, quantity and duration to bedynamically adjusted. In various embodiments, this capability can assistin simulating the light quality changes that occur at dusk and dawn orthe cloud passage, sun flecks in plant canopies or other suchsituations.

In various embodiments, environmental parameters can be adjusted toallow for the study of photosynthetic properties of the plants 122 underreal-world conditions. Such conditions include, for example, partlycloudy days with rapidly changing levels of direct illumination, windydays, humid days, warmer or cooler days, air content and/or combinationsof conditions. In one embodiment, the position, number and/or intensityof lights 112 are adjusted. In one embodiment, the position and/ornumber of cameras 114 are additionally or alternatively adjusted. In oneembodiment, temperature is additionally or alternatively adjusted viamaking adjustments to the heating and cooling apparatus 106. In oneembodiment, humidity and air content are additionally or alternativelyadjusted. Humidity level can be adjusted by regulating the humiditycontrol apparatus 120 while air content can be adjusted by varying thelevel of carbon dioxide 108 and/or oxygen 110 gases flowing into thechamber 102.

In plants, visible and near infrared light affect photosynthetic antennaand stomata development that are linked to photosynthetic efficiency.Phytochromes (through far red light perception) are also thought toimpact stomatal function during dark-light transitions, but not underconstant light. Thus, the ability to alter light quality ratios underfluctuating conditions may result in the isolation of light-dependentcomponents. Given that the plant tradeoff between growth and defensealso appears to have overlapping regulation with shade avoidanceresponses, the ability to alter light quality in the chambers can, inone embodiment, be used for identification and/or examinations offactors related to resource allocation and growth/defense. Further,ultraviolet (UV) irradiation can have strong impacts on plant growth anddefense responses, pigment composition and the induction ofphoto-inhibition of PSII.

Referring again to FIG. 1A, the user 118 is therefore able to controlthe light provided by lights 112, such as to vary the amount ofultraviolet, visible, and infrared light provided to the plant canopy.In a more detailed embodiment, a first set of lights comprise lightsthat emit a broad spectrum of visible and ultraviolet light, closelymimicking field conditions across these spectra. One such example is ahigh color-rendering index (CRI) light-emitting diode (LED) lightprovided by Yuji International, and a second or auxiliary set of lightsproviding supplemental infrared. See also the Example Section, where theeffect of light variations are studied using plants chosen specificallyfor their sensitivity to light variation and quality, such as Camelina.

A variety of parameters from a variety of organisms may be studied orevaluated using the disclosed system and method. In one embodiment, anyphototrophic organism may be studied.

Plants may include monocots and dicots, including, but not limited tospecies such as Arabidopsis, tobacco, soybean, corn, wheat, rice, cottonand various ecotypes, and the like. The plant species further may bemodified by genetic engineering or traditional breeding and alsoincludes plant libraries that have been mutagenized (e.g., T-DNA orchemically). The plants are not limited to any particular developmentstage and may include early stage plant development. Plants may also bewhole plants, plant pans (e.g., stem, leaf), plant preparations (e.g.,thylakoid or other chloroplast preparation), tissue cultures (e.g.,calli or explants), and cell suspension cultures (e.g., single orlumped).

As noted above, measuring chlorophyll fluorescence provides informationon other photosynthetic properties or parameters. Shown below is a tableof the parameters that can be measured and the additional informationthat may be obtained by the disclosed system and method.

TABLE 1 Photosynthetic Characteristics Parameters Reflects MeasuresMeasurement Measures Sensor F_(v)/F_(M) Photosystem Efficiency ofChlorophyll fluorescence II photochemical photosystem II efficiencyphotochemistry LEF Linear electron Rate of photosystem Il Chlorophyllfluorescence flow, calculated electron transfer from incident PAR NPQNonphotochemical The rate of dissipation Chlorophyll fluorescencequenching of adsorbed light energy as heat reflects the fraction ofadsorbed light that is “wasted” as heat. qE Rapidly reversibleEngagement of Chlorophyll fluorescence NPQ component photoprotective NPQresponses qI Long-lived Oxidative Chlorophyll fluorescence NPQphotodamage to and repair of photosystem Il qL Redox status of Backup ofelectrons in Chlorophyll fluorescence photosystem Il photosystem Ilresulting from imbalances in light input, downstream sink capacity andphotoprotection PIFR Postillumination Activation of cyclic Chlorophyllfluorescence recovery of electron transfer via fluorescence the NDHcomplex, engaged under environmental stresses A_(L) Leaf/plant surfaceLeaf area, above- Reflectance area ground biomass and growth dA_(I)/dtChange in Growth rate Reflectance surface area over time LEF_(total)Total plant LEF, Total LEF across the Reflectance and calculated fromplant Fluorescence LEF and AL R_(R) Relative Reflects chlorophyllReflectance reflectance and content and chloroplast adsorptivity of theorientation leaf dR_(R)/dt Change in red Light-induced red Reflectancereflectance as a reflectance changes function of time monitoringchloroplast movements, useful for certain modes of photoprotection T_(L)and T_(S) Leaf and soil Transpiration rate, Thermal imaging temperaturesstomatal aperture and dynamics thereof

In one embodiment, one or all photosynthetic parameters may be evaluatedas any one of the above parameters may be affected by any set of chosenenvironmental conditions.

In addition to the light intensity, light duration and spectralwavelength and quality, the temperature, gases, water or nutrientcontent may be used to evaluate the effect on chlorophyll fluorescence.It should be understood that depending on the parameter to be measuredand evaluated, the enclosures with the appropriate environmental cue andsensor may be configured accordingly. Various genes, gene sets andprofiles (e.g., regulatory genes and the like) ROS production,metabolites, pigments, seed production, biomass, and the like, may alsobe evaluated.

Because stomata in plants such as Camelina are finely regulated tobalance the needs for efficient absorption of carbon dioxide with theavoidance of water loss and the control of pathogens, the dynamics ofstomata regulation are an important field of study for plant growthoptimization. It is believed that the dynamics of stomata regulation(i.e., how rapidly stomata respond to changing conditions) are alsonecessary for this balance, and account for a substantial decrease inphotosynthetic efficiency especially under fluctuating environmentalconditions. Stomata dynamics are thus a prime target for plantimprovement, especially for increasing water use efficiency.

Stomatal dynamics can be monitored non-invasively and in high throughputusing thermal imaging (thermography), which reflects evaporative coolingof leaves resulting from transpiration. Referring again to FIG. 1B, thechamber 102 therefore further includes in some embodiments cameras 114that are operable to observe thermal and/or infrared characteristics ofthe plant canopy. The combination of photosynthesis and thermal imagingdata provided by observing fluorescence and infrared images from theplant canopy can be used to study and characterize plant lines withaltered water use efficiency and defense responses.

The photosystem 100 (FIGS. 1A-1F) can be operable to probe important,photosynthetically-relevant, aspects of the plant architecture byimaging the reflectance of light 112 at specific wavelengths of light.Comparing chlorophyll fluorescence imaging with reflectance imaging suchas red light and/or infrared light reflectance imaging can provide amore accurate estimate of photosynthesis. The spatially resolved datacan also be used, in various embodiments, to indicate regions of theplant in which photosynthesis is limited by light or photosyntheticcapacity. The methods are easily applied to large populations of plants122, either in a chamber 102 (FIGS. 1A-1B) or in field conditions,enabling screening for important photosynthetic properties in many plantlines under diverse environmental conditions. In various embodiments,infrared imaging comprises imaging with infrared, red, or both red andinfrared light (e.g., about 635 nm red and from about 735 to about 1100nm infrared). In one embodiment, chlorophyll fluorescence imaging caninclude extinguishing actinic light for a brief period, such as up toabout 100 milliseconds, and flashing or stimulating the plant canopywith a burst of light such as red light, e.g., measurement light, afterwhich fluorescence can be measured by imaging.

In various embodiments, conditions for capturing images in thephotosystem can be manipulated by altering the number of lightingsources, the location of the lighting sources, the type of lightingsources, the quantity and/or the quality of incident light. In addition,conditions for capturing images in the photosystem can also bemanipulated by altering the sensors such as the cameras, the number ofcameras, the position of the cameras, and the camera filter.

In various embodiments, light sources can be actinic light sources,measurement light sources, and/or infrared light sources. An infraredlight source, together with an actinic light source, can be used toestimate the quantity of actinic light absorbed by the plant canopy.Because the two light sources have a known relative light intensity (bymeans of reflectance standards, known camera response, and/orpreliminary measurement) and a similar light distribution andillumination path, an estimate of the total amount of actinic lightabsorbed by plants can be determined by comparing the amount of actiniclight reflected from plants to that of the infra-red light reflected.

Visible light, and especially in the red and blue regions, is stronglyabsorbed by plant leaves because of the presence of chlorophyll,carotenoids, anthocyanins and other plant pigments. In one embodiment,the actinic light source can generally be the dominant light sourcedriving photosynthesis in the plant canopy, i.e., photosyntheticallyactive radiation or PAR. The intensity measured by an imager of PARscattering from a leaf surface reflects a number of factors. Thesefactors can include the intensity of the incident light, the extent theleaf pigments absorbed the specific wavelengths range of light used, thedistance from the leaf to the imager and the angle of the leaf withrespect to the incident light and the camera.

On the other hand, near infrared light is not strongly absorbed by theleaf and is instead strongly scattered in a Lambertian fashion, i.e.,back scattering of light from the illuminated surface leaf follows asinusoidal pattern. The intensity measured by an imager of near infrared(from about 700 nm to about 1000 nm) backscattering from a leaf surfacereflects a smaller number of factors, mainly reflecting the incidentlight intensity, the distance from the leaf to the imager and the angleof the leaf with respect to the incident light and the camera. Images ofthe backscattered light taken in the visible range with that in the nearinfrared can be used to estimate the amount of light that is absorbed bythe leaf. It can also be possible to use light pulses to measure theefficiency of photosynthesis. In this case, fluorescence fromchlorophylls rather than reflectance is probed using a “measuring light”of one wavelength in the region of PAR and measuring the light emittedby the plant parts at wavelengths where chlorophyll emits fluorescence(from about 680 nm to about 800 nm).

The measurement light source can be any light source that can inducechlorophyll fluorescence in a plant canopy. The light from themeasurement light source can be partially absorbed by the plant. Anamount of the light absorbed by the plant is converted to a differentwavelength by means of chlorophyll fluorescence and is emitted from thecanopy. The fluorescence emitted from the plant canopy, under variouslighting conditions, can be used to determine an estimate of Phi-2 (thequantum yield of photosystem II).

FIGS. 2A-2K are schematic illustrations of various embodiments anddetails of photosystem 100 showing manipulation of the components suchas lighting sources and sensors, such as cameras, in various embodimentsto obtain information regarding photosynthetic parameters in a plantcanopy. In FIGS. 2A-2K, light sources may be referred to or exemplifiedas light source 212 but it is understood that the light sources can belights 212 and/or auxiliary lights 213. The incident light from a lightsource is indicated by bold arrows. Light emitted or reflected by theleaves of the plant or canopy is shown in dashed arrows directed towarda camera.

In one embodiment, FIG. 2A shows photosystem 100 with light source 212and an imaging camera 214. In one embodiment, light source 212 of FIG.2A is an actinic light source that is a broad-spectrum light source.Leaf 204 absorbs some of the light and reflects the remaining light.Camera 214 can be used to acquire images and the specific imagescaptured can be dependent on the selection of filter 214 c.Synchronization of light source 212 and camera 214 can also be used tocapture images.

In another embodiment, lights 212 of FIG. 2A can be a measurement lightsource that emits in the region of PAR with a characteristic wavelengthor distribution λ₁, e.g., 630 nm, and is used to illuminate leaf 204containing fluorescent pigment 204′ that can absorb some of the energyfrom light source 212. An imaging sensor with appropriate sensitivity inthe near infrared, but not sensitivity in the PAR region, is used tomeasure the amount of chlorophyll fluorescence emitted by leaf 204. Anamount of the light absorbed by leaf 204 can be converted to a differentwavelength or distribution, λ₂, by means of chlorophyll fluorescence andis emitted from leaf 204 and captured by camera 214 equipped with filter214 c capable of capturing an image of the emitted light of wavelengthor distribution λ₂. In these embodiments, where energy is absorbed byleaf 204, wavelength or distribution of λ₂ is typically greater(indicating less energy) than the wavelength or distribution of λ₁(indicating greater energy).

Camera 214 of FIG. 2A can include an adjustable camera system asillustrated in FIG. 2B. In one embodiment, camera 214 can be raised orlowered relative to leaf 204 enabling the image to be captured at apoint closer to leaf 204 or farther away from leaf 204. Moving camera204 closer to leaf 204 may expose plant 204 to an increase in theintensity or quantity of light that leaf 204. Camera 214, in oneembodiment, may also be moved laterally, closer to light source 212 orfarther away from light source 212. Lateral movement of camera 214 awayfrom light source 212 can affect the angle and the intensity of thecaptured image.

Multiple camera angles can be used to gain additional data on thestructure of the canopy. Complex plant canopies can result in occlusionso that leaves at the top of the canopy block the view of those at thebottom, preventing measurement of the characteristic of leaves at thebottom of the canopy. By taking images at multiple angles, informationregarding under-canopy leaves can be obtained. In one embodiment, imagesfrom a range of angles using multiple camera angles can be used toobtain a reasonable representation of the canopy. Increasing the numberof images obtained at different angles can increase the accuracy of therepresentation of the canopy.

In one embodiment, the images captured at different angles can be asclose in time as possible to avoid interference from leaf movements.

In one embodiment, multiple cameras can be used to obtain multiplecamera angles. Statistical analyses may be performed to combine the datafrom the multiple cameras to gain a reasonable estimate of theproperties of the plant parts. In one embodiment, multiple angles can beobtained by moving the camera and analyses of the images can beperformed to combine the data from the images at the different angles.

FIG. 2C shows an embodiment demonstrating that the measurement ofreflectance of light by leaf 204 exposed to light from light source 212can be used to determine the amount of absorbed light. Light source 212can emit multiple wavelengths of light, e.g., in the PAR and the nearIR, with the same trajectory or directionality. In other words, the nearIR and the actinic PAR have the same or similar angles with respect tothe plant canopy.

In FIG. 2C, light source 212 emits an initial quantity, x, of lightdirected at leaf 204. Light source 212 can be, in various embodiments,an actinic light source and/or an infrared light source. When leaf 204is exposed to light from light source 212, a quantity of light, y, isabsorbed by leaf 204 via fluorescent pigment 204′. The remainingquantity of light, z, not absorbed by leaf 204 is reflected. Measurementof reflected light, z, by camera 214 can be used determine the quantityof absorbed light, y, since the quantity of reflected light, z, isproportional to the quantity of initial or incident light, x directed atleaf 204.

In various embodiments, varying the angle of the light with respect tothe camera can be used to obtain information regarding the under-canopyleaves and obtain information regarding the canopy. In one embodiment,the photosystem 100 can include two different light sources. As shown inFIG. 2D, in one embodiment, the two different light sources can havedifferent light quality and can be, for example, an actinic light source212 a and a measurement light source 212 b. In one embodiment, the twolight sources 212 a and 212 b can have the same light quality. Bothlight sources 212 a and 212 b can be directed to the same area of leaf204. One or more images can be captured by camera 214. Different imagescan be captured by camera 214 by varying the selection of the filter 214c and/or the synchronization of light sources 212 a and 212 b withcamera 214.

FIG. 2E shows the use of light source 212 and camera 214 in anembodiment of photosystem 100 to determine spatial measurements based ontime of flight analysis. Light source 212 and camera 214 are asindicated and the resultant path of the incident light and emitted lightare as shown. In this embodiment, time of flight data can also bemeasured to obtain distance, d1, between light source 212 and leaf 204and distance, d2, between leaf 204 and camera 214. The angle, θ, betweenleaf 204 and camera 214 is determined by the positioning of the camerawith respect to the imaging detector. The camera is the imaging detectorand the leaf angle can be determined by analysis of the time of flightinformation.

In one embodiment, FIG. 2F shows that light intensity measured by camera214 can be dependent on orientation of leaf 204 relative to light source212. Incident light from light source 212 results in a vector field oflight emitted from leaf 204 based on the orientation of the surface ofleaf 204. The effect of the multiple light angles is to illuminatedifferent sub-sections in the understory leaves and other plant parts.With each angle, different understory leaves and parts of the leaveswill be shaded or exposed to the illuminating light. Comparing imagestaken from each angle will reveal the depth of understory plant partswith respect to the top canopy leaves.

FIG. 2G illustrates an embodiment using multiple cameras to imagedifferent views of the plant or plant canopy. In FIG. 2G, three cameras214 are positioned at different locations and incident light path isshown from light source 212. Multiple leaves 204 of the plant or plantcanopy are shown. Top leaf 204 a, for example, can block some of theincident light and/or emitted light from bottom leaf 204 b. Each ofcameras 214 can be used to image different views of the plant canopy,wherein the light paths can be shown blocked in some images from cameras214 but not in others dependent on the location of the camera placement.The effect of the multiple camera angles is to image differentsub-sections the understory leaves and other plant parts. With eachangle, different understory leaves and parts of the leaves will beexposed to the imaging sensor. Comparing images taken from each anglewill reveal the depth of understory plant parts with respect to the topcanopy leaves.

In a further embodiment, FIG. 2H shows light source 212 a, 212 b, and212 c follow the same path to expose the same area 204′ on leaf 204.Each of light sources 212 a, 212 b, and 212 c can be different or sametypes or quality of light. In one embodiment, light source 212 a can bean infrared light source, light source 212 b can be a measurement lightsource, and light source 212 c can be an actinic light source. Invarious embodiments, the measurement light source can be any fluorescentexcitation light source such as visible light, e.g., red light orultraviolet light. In this embodiment, the angular dependence of theimages can be compared with the reflectance backscatter in the PAR andnear infrared regions to provide a refined estimate of the absorbedlight throughout the plant canopy. This approach can allow estimation ofboth the degree of occlusion at different angles as well as the angulardependence of reflectance of the measuring light with respect to theplant parts. In turn, these results can be analyzed using Lambertianbehavior of plant leaves to light, to determine the curvature and/orplanarity of the leaves as well as the degree of light absorption by PARrelative to the near infrared.

In one embodiment of photosystem 100, FIG. 2I shows that the lightingsources can be placed in two different positions to illuminate differentleaves or leaf portions of a canopy. In some lighting positions, leavesmay or may not be illuminated. By using multiple lighting positions,multiple images can be captured of the canopy for development of thephotosynthesis 3D modeling. As shown in FIG. 2I, leaves 204 a, 204 b and204 c are exposed to incident light from light source 212 a and 212 b.Camera 214 can be used to capture images and includes emitted light frommultiple leaves. Leaves 204 a and 204 c can be, for example, exposed toincident light from light source 212 b whereas portions of leaf 204 bcan be exposed to incident light from only light source 212 a. Thecompilation of images obtained from camera 214 provides informationregarding leafs 204 a, 204 b and 204 c.

In one embodiment, FIG. 2J shows the use of a reflectance and/orfluorescence standard in a canopy to quantify the amount of lightreaching the canopy. By measuring the amount of incident light fromlight source 212 a reaching reflectance standard 254 while knowing thereflectance of the reflectance standard 254, the quantified response forcamera 214 can be determined. As such, the light emitted fromleaf/canopy 204 to camera 214 is quantified and can be compared to theincident light toward canopy 204. In this embodiment, a standardleaf-shaped object with known geometry and optical properties is placedwithin the chamber to provide a means of standardizing or normalizingthe results. The standard can have reflectance and fluorescentproperties that mimic the plant materials and can be placed both in theopen (without obstructions) and within the plant canopy, to provide avalidation of the measurements.

In one embodiment of photosystem 100, FIG. 2K shows multiple lightsources and multiple cameras that can be modulated to provide differentunderstory illumination and camera angles to determine the efficiency ofphotosynthesis throughout the plant canopy. This can provide a moredetailed representation of the plant canopy. Light source 212 a, lightsources 212 b and light source 212 c can be, for example, the infraredlight source, measurement light source and the actinic light source,respectively, with leaf 204 exposed to all three light sources. Cameras214 d, 214 e and 214 f can be used, for example, to capture images fromlight sources 212 a, 212 b and 212 c. In one embodiment, a single cameramay also be used to capture images resulting from light sources 212 a,212 b and 212 c.

The lights, cameras, and other components that simulate varying weatherconditions such as humidity, gases, wind, heating and cooling may bemanipulated and images captured to provide information related to 3Dphotosynthetic parameters in a plant or a plant canopy.

FIG. 3 is a flowchart illustrating an example method of estimatingefficiency of photosynthesis in a plant canopy. Here, plants are placedin a chamber at 302, such as the chamber 102 of FIG. 1A or in a fieldthat is configured for observation. Two-dimensional infrared images arecollected at 304, and two-dimensional Phi-2 fluorescence imaging iscollected at 306. The infrared images are used not only for plantcharacteristic measurements such as light/dark transition measurements,but for determining the size and position of the leaves of plants 122that make up the plant canopy and contribute to photosynthesis. Theinfrared data is therefore collected at 308, which in some embodimentscomprises multiple images of the same region of the plant canopy fromdifferent angles. These multiple images are then used to generate anglemodeling of the leaves that make up the plant canopy at 310, as well asto model the depth of the plant canopy at 312, such as where multiplelayers of leaves have varying degrees of exposure to illumination fromabove.

Various geometric parameters of the plant canopy and configuration, aswell as the configuration of the cameras (and lighting in someembodiments) as shown at 314 are used along with the depth modeling datagenerated at 312 to generate a camera model 316 and light model 318.These models of depth and angle of plant foliage, as well as position oflighting and cameras, are then used to generate an approximation of a 3Dmodel at 320.

More specifically, knowing the angle of a plant leaf relative to one ormore lights enables calculation or estimation of the amount of lightreaching the leaf from each of the lights such as 112. A leaf that isperpendicular to the direction of travel of light will receive a fulldose of light across the surface of the leaf, while tilted leaves willreceive less light depending on the angle of tilt, calculated such as bymultiplying the light intensity by the cosine of the angle between thedirection of light travel and the tilt of the leaf. Angles such as theseare modeled at 310 in this embodiment, while calculations based on theangle modeling are performed at 320.

Similarly, the distance from each light to each leaf is also employed todetermine the amount of light reaching each leaf, based on the distancefrom the light to the leaf and the brightness of the light. This isreflected by depth modeling at 312 in this example, where a model of thedepth from light sources to modeled leaves are determined based onfactors such as the geometry of the growth chamber at 314 and theinfrared or other measurements at 308. Distance information in a furtherembodiment is determined using time-of-flight measurements, such as bysending a light such as a laser, or another signal such as an ultrasonicpulse, from a device such as a camera 114 to the plant canopy andobserving the time taken to receive a return signal. In otherembodiments, interferometry or other signal processing techniques areemployed to measure time of flight, or to otherwise measure distancefrom a known location to one or more leaves in the plant canopy.

Once an accurate model of the lighting and camera configuration are usedto generate an accurate model of the leaf configuration, thethree-dimensional models are used to model characteristics of the plantcanopy at 320, such as photosynthetic efficiency. In a furtherembodiment, this is based at least in part on observed two-dimensionalPhi-2 fluorescence image data obtained at 306 and stored at 322, such asimaging the chlorophyll fluorescence of the leaf canopy very shortlyafter turning off actinic light provided to the plants being studied, ormeasuring fluorescence very shortly after turning off a pulsed light orstimulating light provided to the plant canopy soon after (e.g., 200milliseconds after) extinguishing actinic light. In other embodiments,other methods such as radiometry, color spectrometry, and infrared orthermal imaging are employed to measure one or more plantcharacteristics such as photosynthetic efficiency or activity.

Here, the three-dimensional linear electron flow (LEF) modelingperformed at 320 is based on the observed two-dimensional Phi-2fluorescence image data 322, which indicates the absorption of light byantennae complexes that funnel the light energy into photosystems withinthe plants. The plant photosystems oxidize H₂O and reduce NADP⁺ to NADPHin a process called linear electron flow (LEF), which is modeled todetermine the rate or efficiency of photosynthesis in the plants.Because light absorbed by chlorophyll molecules in a plant leaf areeither used to drive this photosynthesis process, are dissipated asheat, or are re-emitted as chlorophyll fluorescence, measurement of aplant's chlorophyll fluorescence can be used along with otherinformation such as the amount of light striking the leaf to estimatethe efficiency of photosynthesis (and consequently, photosynthesischaracteristic elements such as linear electron flow).

In the embodiment of FIG. 3, a complete traditional three-dimensionalmodel need not be created, as the depth and angle information along witha geometric model including camera and light information can be used toestimate the area of each leaf of the canopy and compensate for anyeffects due to varying angles or positions of the leaves, cameras, andlighting. This enables accurate modeling of the plants 122 withoutcreating a complete traditional three-dimensional model of the plantcanopy and surrounding environment, typically employing complex mathsuch as ray tracing and shading that are very computationally intensive.The method of estimating photosynthetic efficiency of FIG. 3 does notrequire such computationally complex steps, and so is more readilyemployed using relatively inexpensive systems such as a personalcomputer as the computerized system 116 performing the functions recitedin FIG. 3.

FIGS. 4A and 4B are false color plant images (with black backgroundremoved for simplicity), used to estimate photosynthetic electrontransfer rate, i.e., efficiency (See FIGS. 4C-4F). FIGS. 4A′-4F′ areschematic representations of the images of FIGS. 4A-4F, with thedifferent fills intended to roughly correspond to the different colorsobtained with the imaging and modeling. This estimation can be achieved.by multiplying estimates of photochemical efficiency by the rate ofabsorbed PAR over the entire surface of the plant. Photosyntheticefficiency can be determined by multiplying Phi-2, measured by imagingchlorophyll fluorescence (FIG. 4A) and the IR-reflectance (FIG. 4B), andthen comparing Phi-2 image and the IR reflectance image (FIGS. 4A and4B), with measuring lights that have the same trajectories.

In FIG. 4A, a plant is illuminated from a single direction using asingle camera perspective to produce a false-color image primarilyorange in the center with yellow to yellow/green on the leaves. Themeasuring light source can be placed so that it illuminates the plantswith light that has the same general angular dependence. In oneembodiment, the measuring light source is perpendicular to the groundwith a divergence of about 5 to about 15 degrees, such as about 8 to 12degrees, such as no more or no less than about 10°. Measurements canthen be made of Phi-2 fluorescence (FIG. 4A), and the differentialreflectance of infrared and PAR light (FIG. 4B) reflecting the amount oflight absorbed by the leaf at each pixel position (with color bluerepresenting low levels to color red representing high levels). FIGS.4C-4F show the calculation of the LEF from the fluorescence-derivedimages of Phi-2 and reflectance.

As light is known through controlling light or measurement in fieldconditions, various calculations can be performed using light,reflectance, and Phi-2 fluorescence as shown in the remaining images.For example, the bottom center (FIG. 4E) image shows reflectancemultiplied by light, which given a relatively even distribution of lightstrongly resembles reflectance as shown at top center (FIG. 4B).Reflectance multiplied by Phi-2 fluorescence is shown at top right (FIG.4C), indicating how photosynthetic efficiency and light distributionoverlap. Lastly, the bottom right image (FIG. 4F) shows Phi-2fluorescence multiplied by reflectance and light intensity, to produce acorrected image of LEF that takes into account uneven distribution oflight across the plant canopy. The upper right image shows the simple(current state of the art) image of LEF estimated by multiplying Phi-2images by the average light intensity, without regard to differences inthe degree of light absorption by different plant parts. The bottomright image shows Phi-2 fluorescence multiplied by the estimated lightabsorbed using the reflectance procedure as described herein,illustrating the fact that the LEF is determined more accurately whenthe light absorbance is taken into account.

The embodiment in FIGS. 5A-5D shows the steps used to render athree-dimensional leaf model used to estimate photosynthetic efficiency,with FIGS. 5A′-5D′ providing a schematic representation of the images inFIG. 5A-5D, with the different fills intended to roughly represent thedifferent colors obtained through the imaging and modeling. FIG. 5Ashows depth image of a plant, such as may be employed at 312 of FIG. 3.The depth image (FIG. 5A) is based on two-dimensional imaging, such asinfrared imaging of the plant. In one embodiment, the two-dimensionalimage may be based on a time of flight imaging sensor(s) or othersensor(s) operable to detect position of various points on the surfaceof the plant leaves. In FIG. 5B, a plot of points on the various plantleaves is presented in three dimension, such that the points on theleaves shown can be processed using software configured to recognizeleaf shapes among images and segment images such as the point cloud intoindividual leaves. The individual leaves are shown in FIG. 5C with adifferent color representing each distinct leaf. FIG. 5D shows theresulting three-dimensional model of each leaf, including leaf angle andshape, such that surface area and angle of light incidence of eachportion of each leaf are modeled. This modeling enables calculation ofphotosynthetic efficiency based on variations in illuminating light ormeasured fluorescence, taking into account the angle of each leaf,shading provided by other leaves, and other such factors.

In a more complex example, leaf shapes, angles, and densities can beused to provide other important information about a leaf canopy, such asthe efficiency of the canopy at presenting leaves having highphotosynthetic efficiency to proper light conditions. Light penetrationthrough such a canopy may be limited to varying degrees, and is furthermodeled in some complex examples such as by characterizing the lightreaching various depths of a canopy or by machine learning algorithms toaccount for leaf surfaces that are occluded by intervening material inthe plant canopy.

FIG. 6 is a flowchart of an example method of estimating thephotosynthetic efficiency of plants. At 602, plants are set up in thetest chamber (such as chamber 102 of FIG. 1) for measurement. In anotherembodiment, plants are measured in the field, or on location such as ina greenhouse. Next, cameras, lighting, and other geometric configurationinformation is obtained at 604, including distance from source light toplants, distance from the camera or cameras to the plants, and othersuch parameters. Two-dimensional images are then captured at 606,including plant fluorescence or Phi-2 images, and infrared reflectanceimages. In one embodiment, red reflectance images may also capturedalong with Phi-2 images, and infrared reflectance images. These capturedimages are processed at 608 to extract pixel-level data of the images,representing the image information captured corresponding to variouspoints on the leaves of the plants. The depth of leaves is then modeledat 610 from geometric parameters determined at 602, and from infraredpixel-level data determined at 608. The angle of leaves is furthercalculated at 612, based on pixel-level infrared reflectance datadetermined at 608. A more detailed example of steps 606-612 is shown inFIG. 5.

Next, the light intensity striking each leaf is modeled at 614 using thegeometric parameters determined at 604, and the depth informationdetermined at 610. Camera mapping is further calculated at 614 using thegeometric parameters determined at 604 and the depth informationdetermined at 610, which includes mapping the images taken at 606 ontothe geometric plant leaf models generated at 608-612. The resultingthree-dimensional plant leaf model and mapped image data are used tomodel linear electron flow (LEF) or another characteristic ofphotosynthesis efficiency at 616, using information including thetwo-dimensional plant fluorescence image data captured at 606, angleinformation from 612, leaf geometry modeling from camera mapping at 614,and light intensity information from 614. A more detailed example of 616is shown in FIG. 3.

The resulting photosynthesis efficiency information is then output, suchas being provided as an image having shading or coloring representingthe photosynthetic efficiency of the imaged leaves in the plant canopy.Such images enable easy, rapid and more accurate visualization ofphotosynthetic efficiency of various parts of a plant, and plants havingdifferent characteristics such as different genotypes or that have beensubject to different environmental conditions.

The method described here results in an efficient and accurate estimateof photosynthetic efficiency of a plant or group of plants, withoutrequiring building a complete three-dimensional model of each plant andits environment. The technique in some examples images the reflectanceof plant canopies using infrared (750-940 mm) and/or red (about 635 nm)light having the same optical incident geometry as the actinic lightprovided to stimulate photosynthesis. The reflectance measurements areanalyzed using a fitting equation to estimate the fraction of actiniclight absorbed by the leaves. Comparison of reflectance measurements inthe red and infrared spectrums can be used to assess the effects ofaltered chlorophyll content and chloroplast movements.

Photo-induced electron transfer or LEF can be estimated by multiplyingPhi-2 (measured by chlorophyll fluorescence imaging) with estimatedabsorbed light, and output as an image representing linear electron flowusing color or tone gradients. Combining data from multiple cameras frommultiple angles compensates for variations in leaf movements, growthheight, and other such complications that might hinder accuracy inenvironments where a single optical perspective is used. Furthercorrection for shaded or occluded regions of the plant canopy can bemodeled using prior measurements, machine learning algorithms, or othersuch data to provide more accurate estimates of photosynthesis for theplants, even if such lower layers of leaves are not a part of thethree-dimensional model used to characterize efficiency ofphotosynthesis.

In other embodiments, a single camera or a group of cameras may be sweptacross a plant canopy, such as by changing the angle of a stationarycamera or by moving a camera across a plant canopy to collect imagesfrom multiple angles. The distance from the camera to the plant canopyis in some embodiments limited, to preserve high pixel resolution datafor the various leaves making up the plant canopy and to facilitateaccurate measurement of distance to the plant canopy, angles of theplant leaves, and other such information.

Distance to plant leaves is estimated in some embodiments by use ofinfrared time-of-flight cameras, or by other suitable means such aslaser interferometry. In one embodiment, a camera system such as anIntel Senz 3D infrared time-of-flight camera is used to measure time offlight from the camera to the leaves making up the plant canopy, andoptionally a more accurate method such as laser interferometry or otherphysical measurement is used to verify the camera data.

Although some embodiments presented herein focus on studying differencesbetween various plants, the environmental conditions in which the plantsgrow may be varied, such that their effect on photosynthesis can bemeasured or characterized. In one embodiment, wind may be applied to theplant canopy via one or more fans to simulate the effect of leavesfluttering in the wind, as fluttering leaves may have differentphotosynthetic efficiency characteristics than still leaves.Additionally or alternatively, light conditions may be varied on theseconds or minutes scale to simulate partly cloudy days, such as whenclouds pass overhead shading plants but soon blow past restoring directsunlight.

The methods described herein, such as are illustrated in FIGS. 3 and 6,may be implemented in whole or in part in a computerized system in someembodiments. FIG. 7 shows one embodiment of a computerizedphotosynthesis modeling system comprising a computing device 700.Although computing device 700 is shown as a standalone computing device,computing device 700 may be any component or system that includes one ormore processors or another suitable computing environment useful forexecuting software instructions, and need not include all of theelements shown here.

In the embodiment shown in FIG. 7, computing device 700 includes one ormore processors 702, memory 704, one or more input devices 706, one ormore output devices 708, one or more communication modules 710, and oneor more storage devices 712. Computing device 700, in one embodiment,further includes an operating system 716 executable by computing device700. The operating system may include various services, such as anetwork service 718 and a virtual machine service 720, such as a virtualserver. One or more applications, such as photosynthesis estimationmodule 722 may also be stored on storage device 712, and be executableby computing device 700.

Each of components 702, 704, 706, 708, 710, and 712 may beinterconnected (physically, communicatively, and/or operatively) forinter-component communications, such as via one or more communicationschannels 714. In some embodiments, communication channels 714 include asystem bus, network connection, inter-processor communication network,or any other channel for communicating data. Applications such asphotosynthesis estimation module 722 and operating system 716 may alsocommunicate information with one another as well as with othercomponents in computing device 700.

In one embodiment, processors 702 are configured to implementfunctionality and/or process instructions for execution within computingdevice 700. In one embodiment, processors 702 may be capable ofprocessing instructions stored in storage device 712 or memory 704. Invarious embodiments, processors 702 may include any one or more of amicroprocessor, a controller, a digital signal processor (DSP), anapplication specific integrated circuit (ASIC), a field-programmablegate array (FPGA), or similar discrete or integrated logic circuitry.

One or more storage devices 712 may be configured to store informationwithin computing device 700 during operation. In one embodiment, storagedevice 712 is known as a computer-readable storage medium. In variousembodiments, storage device 712 comprises temporary memory, meaning thata primary purpose of storage device 712 is not long-term storage. Invarious embodiments, storage device 712 is a volatile memory, such thatstorage device 712 does not maintain stored contents when computingdevice 700 is turned off. In other embodiments, data is loaded fromstorage device 712 into memory 604 during operation. In variousembodiments, volatile memories can include random access memories (RAM),dynamic random access memories (DRAM), static random access memories(SRAM), and other forms of volatile memories known in the art. In oneembodiment, storage device 712 is used to store program instructions forexecution by processors 702. In other embodiments, storage device 712and memory 704, are used by software or applications running oncomputing device 700 such as recommendation module 722 to temporarilystore information during program execution.

In various embodiments, storage device 712 includes one or morecomputer-readable storage media that may be configured to store largeramounts of information than volatile memory. In one embodiment, storagedevice 712 may further be configured for long-term storage ofinformation. In one embodiment, storage devices 712 include non-volatilestorage elements. Examples of such non-volatile storage elements whichmay be used herein, include, but are not limited to, magnetic harddiscs, optical discs, floppy discs, flash memories, or forms ofelectrically programmable memories (EPROM) or electrically erasable andprogrammable (EEPROM) memory

In various embodiments, computing device 700 also includes one or morecommunication modules 710. In one embodiment, computing device 700 usescommunication module 710 to communicate with external devices via one ormore networks, such as one or more wireless networks. In variousembodiments, communication module 710 may be a network interface card,such as an Ethernet card, an optical transceiver, a radio frequencytransceiver, or any other type of device that can send and/or receiveinformation. Other examples of such network interfaces which may beuseful herein include, but are not limited to, Bluetooth, 3G or 4G, WiFiradios, and Near-Field Communications (NFC), and Universal Serial Bus(USB). In various embodiments, computing device 700 uses communicationmodule 610 to wirelessly communicate with an external device such as viaa public network.

In one embodiment, computing device 700 also includes one or more inputdevices 706. In various embodiments, input device 706 is configured toreceive input from a user through tactile, audio, or video input.Examples of input device 706 useful herein include, but are not limitedto, a touchscreen display, a mouse, a keyboard, a voice responsivesystem, video camera, microphone or any other type of device fordetecting input from a user.

One or more output devices 708 may also be included in computing device700. In various embodiments, output device 708 is configured to provideoutput to a user using tactile, audio, or video stimuli. In oneembodiment, output device 708 includes, but is not limited to, adisplay, a sound card, a video graphics adapter card, or any other typeof device for converting a signal into an appropriate formunderstandable to humans or machines. Additional examples of outputdevice 708 useful herein, include, but are not limited to, a speaker, alight-emitting diode (LED) display, a liquid crystal display (LCD), orany other type of device that can generate output to a user.

In one embodiment, computing device 700 includes operating system 716.In various embodiments, operating system 716 controls the operation ofcomponents of computing device 700, and provides an interface fromvarious applications such as photosynthesis estimation module 722 tocomponents of computing device 700. In one embodiment, operating system716 facilitates the communication of various applications such asrecommendation module 722 with processors 702, communication unit 710,storage device 712, input device 706, and output device 708.Applications such as photosynthesis estimation module 722 may include,in various embodiments, program instructions and/or data that areexecutable by computing device 700. In one embodiment, photosynthesisestimation module 722 and its imaging module 724, calculation module726, and output module 728 may include instructions that cause computingdevice 700 to perform one or more of the operations and actionsdescribed in the examples presented herein.

Any suitable image processing software (hereinafter “software”) whichcan display, edit, analyze, process, save, and optionally print images,such as 8-bit color and grayscale, 16-bit integer, and 32-bit floatingpoint images, can be used. In one embodiment, the software can readmultiple types of image file formats, including, but not limited to,TIFF, PNG, GIF, JPEG, BMP, DICOM, and FITS, as well as RAW formats. Inone embodiment, the software can support image stacks, i.e., a series ofimages that share a single window. In one embodiment, the software ismultithreaded, so otherwise time-consuming operations can be performedin parallel on hardware having multiple central processing units (CPUs).In one embodiment, the software can calculate area and pixel valuestatistics of user-defined selections and intensity-thresholded objects.In one embodiment, the software can measure distances and angles. In oneembodiment, the software can create density histograms and line profileplots. In one embodiment, the software supports standard imageprocessing functions, such as logical and arithmetical operationsbetween images, contrast manipulation, convolution, Fourier analysis,sharpening, smoothing, edge detection, and median filtering. In oneembodiment, the software performs geometric transformations such asscaling, rotation, and flips. In one embodiment, the software supportsany number of images simultaneously, limited only by available memory.In one embodiment, ImageJ software, a Java-based image processingprogram developed at the National Institutes of Health, is used. In oneembodiment, the software allows custom acquisition, analysis andprocessing plugins to be developed using the software's built-in editorand a Java compiler. User-written plugins make it possible to solve manyimage processing and analysis problems, such as multiple imaging systemdata comparisons.

The chlorophyll fluorescence profiles or any of the data generated underthe varying environments for the test phototrophic organisms may be usedto generate databases or data may be compared to other phototrophicorganisms and also may be used to generate photosynthetic “signatures.”

Reference is now made to the following example, which is offered tofurther describe various embodiments of the present invention. It shouldbe understood, however, that many variations and modifications may bemade while remaining within the scope of the present invention.

Example

A single sample of a Camelina plant obtained from the plant growthfacilities at Michigan State University Plant Research Lab was placedinto a photosystem comparable to photosystem 100 and imaged under 25°C., relative humidity of approximately 65% and illumination conditionsdescribed below.

The sample was illuminated under actinic lighting (white BridgeluxBXRA-56C5300 LEDs purchased from Newark Electronics) at aphotosynthetically active radiation (PAR) of 300 umol/m²s⁻¹. Phi-2 imageacquisition was accomplished by arithmetically processing the acquiredimages to determine Phi-2, based on the relation:

Phi-2=F′v/F′m=(F′ _(m) −F _(s))/F′ _(m)

wherein F′_(m) is the maximum fluorescent yield of a light adapted plantafter a saturating pulse; F′v/F′m is the quantum yield of a lightadapted plant, Fs is the steady state fluorescence yield of a lightadapted plant, no saturating pulse F′v is simply F′m−Fs. A saturatingpulse is an intense pulse of actinic light that completely saturatesphotosystem-II.

The F_(s) image was captured by adapting the plant under actiniclighting at 300 umol/m² s¹, whereby the actinic light was turned off forapproximately 100 μs. During this off-time, the 630 nm measurement light(provided by Luxeon Rebel SMT High Power LEDs Red, LXM2-PD01-0050,Philips Lumiled, San Jose, Calif.) was turned on for approximately 50 μsto induce fluorescence.

The resulting fluorescence was captured with a color-filtered (SchottRG-9 colored glass filter, Edmund Optics) CCD camera (KPV145MC, Hitachi,Chiyoda, Japan Hitachi) (hereinafter “Hitachi camera system”) which onlyaccepts the fluorescence or IR-reflectance signal and blocks themeasuring light. The F′_(m) image was captured by exposing the plant toa saturating pulse with an intensity of ˜15,000 umol/m² s¹ to completelysaturate photosynthesis using actinic light, followed immediately byexposure to an approximately 630 nm measurement light (approximately 50μs duration), which illuminated the plant to induce fluorescence. Theresulting fluorescence was captured with the Hitachi camera system.

The resulting false color images shown in FIGS. 8A and 8B (with theblack background removed for simplicity) were operated onarithmetically, using commercially available software (ImageJSoftware®), to obtain the resulting (F′_(m)−F_(s))/F′_(m)→Phi-2 Image(FIG. 8C). FIGS. 8A′-8C′ provide schematic representations of the imagesin FIG. 8A-8C, with the different fills intended to roughly representthe different colors obtained through the imaging and modeling.

To obtain the IR-Reflectance image, the same Camelina plant was exposedto an approximately 940 nm LED light (SFH 4725S, Osram OptoSemiconductors, Inc., Regensburg, Germany) for 50 μs while the Hitachicamera system captured the reflected light.

By weighting the original Phi-2 (LEF) (FIG. 8A) image with an estimateof the incident PAR (IR-Reflectance image, FIG. 8B), the resulting image(FIG. 8C) more accurately shows the relative intensity of LEF. FIG. 8Cshows that the amount of LEF is dependent on the amount of lightreaching the various locations in the canopy. This light dependentvariability is apparent in the resulting Phi-2 (LEF) multiplied byIR-Reflectance image (FIG. 8C), on the right, but not so in the originalPhi-2 (LEF) image (FIG. 8A).

In one embodiment, a method of determining photosyntheticcharacteristics in one or more plants is provided. The method comprisingcapturing a plurality of images of plant parts in said plants with oneor more sensors, wherein the plurality of images comprises a first imagecomprising measurement of the fluorescence of the plant parts of saidplants and a second image comprising capture of reflectance images ofthe plant parts in said plants upon exposure to a light(s). The methodfurther comprises deriving information regarding a characteristic ofphotosynthesis of the plant parts of said plants by multiplying theplurality of images.

In one embodiment, the method is provided wherein the multiplying theplurality of images comprises multiplying the first image with thesecond image.

In one embodiment, the method is provided wherein one of the pluralityof images captures absorbance by the plant parts in said plant uponexposure to the light.

In one embodiment, the method is provided wherein the method furthercomprises capturing additional images wherein the conditions forcapturing the additional images are altered relative to the conditionswhen capturing the first image and the second image.

In one embodiment, the method is provided wherein the conditions areselected from location of the sensors, the number of sensors, a filteron the sensor, the number of the lights provided, the quality ofprovided light(s), location(s) of the provided light(s) and combinationsthereof.

In one embodiment, a method of characterizing photosynthesis in one ormore plants is provided. The method comprising capturing a plurality ofimages of the one or more plants with a sensor, generating athree-dimensional model comprising the plant parts of said plants fromthe plurality of images, measuring fluorescence of the plant parts ofsaid plants and deriving a characteristic of photosynthesis of saidplants using the measured fluorescence of the plant parts of said plantsand the three-dimensional model comprising the plant parts of saidplants.

In one embodiment, the method is provided wherein the three-dimensionalmodel further comprises one or more geometric parameters, comprising atleast one of light position relative to said plants, sensor positionrelative to said plants, and light position relative to sensor position.

In one embodiment, the method is provided wherein the plurality ofimages of said plants comprise infrared reflectance images.

In one embodiment, the method is provided further comprising providinginfrared light to said plants.

In one embodiment, the method is provided further comprising providingred light to said plants.

In one embodiment, the method is provided wherein measuring fluorescenceof the plant parts of said plants comprises removing the provided redlight from said plants, and measuring the fluorescence of the plantparts promptly after removing the provided red light.

In one embodiment, the method is provided, where said plants, thesensor, and one or more lights are disposed in a chamber.

In one embodiment, the method is provided, further comprisingenvironmental controls operable to control at least one of temperature,humidity, oxygen, carbon dioxide, and wind in the chamber.

In one embodiment, the method is provided, further comprising one ormore instruments operable to measure time of flight from the instrumentto the plant parts of said plants.

In one embodiment, the method is provided further comprisingcompensating for multiple layers of plant parts in said plants inderiving a characteristic of photosynthesis of said plants.

In one embodiment, the method is provided further comprising acomputerized system operable to perform the deriving a characteristic ofphotosynthesis of said plants.

In one embodiment, the method is provided wherein deriving acharacteristic of photosynthesis of said plants comprises mappinginformation from the measured fluorescence of the plant parts of saidplants onto the three-dimensional model comprising the plant parts ofsaid plants.

In one embodiment, the method is provided wherein deriving acharacteristic of photosynthesis of said plants further comprisesmapping a light source illuminating the plant parts of said plants ontothe three-dimensional model comprising the plant parts of said plants.

In one embodiment, the method is provided further comprising estimatingthe light absorbed by the plant parts of said plants by at least one ofred light and infrared light reflectance images of the plant parts ofsaid plants, and wherein deriving a characteristic of photosynthesis ofsaid plants further comprises multiplying the measured fluorescence ofthe plant parts of said plants by the estimated light absorbed by theplant parts of said plants.

In one embodiment, the method is provided wherein the plurality ofimages of said plants comprise at least one infrared image and at leastone red image, and wherein a fraction of actinic light absorbed by theplant parts of said plants is estimated by comparing the infrared andred images.

In one embodiment, the method is provided wherein deriving acharacteristic of photosynthesis of said plants comprises mapping alight source illuminating the plant parts of said plants onto thethree-dimensional model comprising the plant parts of said plants.

In one embodiment, the method is provided, wherein deriving acharacteristic of photosynthesis comprises deriving one or more of arate of photosynthesis, efficiency of photosynthesis, and linearelectron flow (LEF) within the plant parts of said plants.

In one embodiment, the method is provided wherein the one or moresensors comprise one or more cameras and the one or more camerascomprise one or more filters mounted on said cameras.

In one embodiment, the method is provided wherein the plant partscomprises one or more leaves.

In one embodiment, a plant photosynthesis characterization apparatus isprovided comprising one or more sensors configured to capture aplurality of images of one or more plants and a computerized systemcoupled to receive the one or more images of said plants from the one ormore sensors, the computerized system operable to generate athree-dimensional model comprising the plant parts of said plants fromthe received plurality of images, to measure fluorescence of the plantparts of said plants, and to derive a characteristic of photosynthesisof said plants using the measured fluorescence of the plant parts ofsaid plants and the three-dimensional model comprising the plant partsof said plants.

In one embodiment, the apparatus is provided wherein thethree-dimensional model further comprises one or more geometricparameters, comprising at least one of light position relative to saidplants, sensor position relative to said plants, and light positionrelative to sensor position.

In one embodiment, the apparatus is provided wherein the one or moresensors comprise infrared sensors and the plurality of images of saidplants comprise infrared reflectance images.

In one embodiment, the apparatus is provided further comprising one ormore lights operable to provide infrared light to said plants.

In one embodiment, the apparatus is provided further comprising one ormore lights operable to provide red light to said plants.

In one embodiment, the apparatus is provided wherein measuringfluorescence of the plant parts of said plants comprises removing theprovided red light from said plants by turning off the one or morelights operable to provide red light, and measuring the fluorescence ofthe plant parts promptly after removing the provided red light.

In one embodiment, the apparatus is provided further comprising achamber, such that said plants, the sensor, and one or more lights aredisposed in the chamber.

In one embodiment, the apparatus is provided further comprising one ormore environmental controls operable to control at least one oftemperature, humidity, oxygen, carbon dioxide, and wind in the chamber.

In one embodiment, the apparatus is provided further comprising one ormore instruments operable to measure time of flight from the instrumentto the plant parts of said plants.

In one embodiment, the apparatus is provided comprising the computerizedsystem further operable to compensate for multiple layers of plant partsin said plants in deriving a characteristic of photosynthesis of saidplants.

In one embodiment, the apparatus is provided wherein deriving acharacteristic of photosynthesis of said plants comprises mappinginformation from the measured fluorescence of the plant parts of saidplants onto the three-dimensional model comprising the plant parts ofsaid plants.

In one embodiment, the apparatus is provided wherein deriving acharacteristic of photosynthesis of said plants further comprisesmapping a light source illuminating the plant parts of said plants ontothe three-dimensional model comprising the plant parts of said plants.

In one embodiment, the apparatus is provided wherein the computerizedsystem further operable to estimate the light absorbed by the plantparts of said plants by at least one of red light and infrared lightreflectance images of the plant parts of said plants, and whereinderiving a characteristic of photosynthesis of said plants furthercomprises multiplying the measured fluorescence of the plant parts ofsaid plants by the estimated light absorbed by the plant parts of saidplants.

In one embodiment, the apparatus is provided, wherein the plurality ofimages of said plants comprise at least one infrared image and at leastone red image, and wherein the computerized system is further operableto estimate a fraction of actinic light absorbed by the plant parts ofsaid plants by comparing the infrared and red images.

In one embodiment, the apparatus is provided wherein deriving acharacteristic of photosynthesis of said plants comprises mapping alight source illuminating the plant parts of said plants onto thethree-dimensional model comprising the plant parts of said plants.

In one embodiment, the apparatus is provided wherein deriving acharacteristic of photosynthesis comprises deriving one or more of arate of photosynthesis, efficiency of photosynthesis, and linearelectron flow (LEF) within the plant parts of said plants.

In one embodiment, the apparatus is provided wherein the one or moresensors comprise one or more cameras.

In one embodiment, the apparatus is provided wherein the one or morecameras comprise one or more filters mounted on said cameras.

In one embodiment, the apparatus is provided wherein the plant partscomprises one or more leaves.

In one embodiment, a non-transitory machine-readable medium withinstructions stored thereon is provided. In one embodiment, theinstructions when executed operable to cause a computerized system tocapture a plurality of images of one or more plants via a sensor, togenerate a three-dimensional model comprising plant parts of the one ormore plants from the plurality of images, to measure fluorescence of theplant parts of said plants and to derive a characteristic ofphotosynthesis of said plants using the measured fluorescence of theplant parts of said plants and the three-dimensional model comprisingthe plant parts of said plants.

In one embodiment, the medium is provided wherein the three-dimensionalmodel further comprises one or more geometric parameters, comprising atleast one of light position relative to said plants, sensor positionrelative to said plants, and light position relative to sensor position.

In one embodiment, the medium is provided wherein the plurality ofimages of said plants comprise infrared reflectance images.

In one embodiment, the medium is provided, the computerized systemfurther operable to control providing infrared light to said plants.

In one embodiment, the medium is provided, wherein the computerizedsystem is further operable to control providing red light to saidplants.

In one embodiment, the medium is provided wherein measuring fluorescenceof the plant parts of said plants comprises removing the provided redlight from said plants, and measuring the fluorescence of the plantparts promptly after removing the provided red light.

In one embodiment, the medium is provided, where said plants, thesensor, and one or more lights are disposed in a chamber.

In one embodiment, the medium is provided, wherein the instructions whenexecuted are further operable to control one or more environmentalcontrols operable to control at least one of temperature, humidity,oxygen, carbon dioxide, and wind in the chamber.

In one embodiment, the medium is provided, wherein the instructions whenexecuted are further operable to control one or more instrumentsoperable to measure time of flight from the instrument to the plantparts of said plants.

In one embodiment, the medium is provided, the instructions whenexecuted further operable to compensate for multiple layers of plantparts in said plants in deriving a characteristic of photosynthesis ofsaid plants.

In one embodiment, the medium is provided, wherein deriving acharacteristic of photosynthesis of said plants comprises mappinginformation from the measured fluorescence of the plant parts of saidplants onto the three-dimensional model comprising the plant parts ofsaid plants.

In one embodiment, the medium is provided wherein deriving acharacteristic of photosynthesis of said plants further comprisesmapping a light source illuminating the plant parts of said plants ontothe three-dimensional model comprising the plant parts of said plants.

In one embodiment, the medium is provided, the instructions whenexecuted further operable to estimate the light absorbed by the plantparts of said plants by at least one of red light and infrared lightreflectance images of the plant parts of said plants, and whereinderiving a characteristic of photosynthesis of said plants furthercomprises multiplying the measured fluorescence of the plant parts ofsaid plants by the estimated light absorbed by the plant parts of saidplants.

In one embodiment, the medium is provided, wherein the plurality ofimages of said plants comprise at least one infrared image and at leastone red image, and wherein a fraction of actinic light absorbed by theplant parts of said plants is estimated by comparing the infrared andred images.

In one embodiment, the medium is provided, wherein deriving acharacteristic of photosynthesis of said plants comprises mapping alight source illuminating the plant parts of said plants onto thethree-dimensional model comprising the plant parts of said plants.

In one embodiment, the medium is provided, wherein deriving acharacteristic of photosynthesis comprises deriving one or more of arate of photosynthesis, efficiency of photosynthesis, and linearelectron flow (LEF) within the plant parts of said plants.

In one embodiment, the medium is provided wherein the one or moresensors comprise one or more cameras and the one or more camerascomprise one or more filters mounted on said cameras.

In one embodiment, the medium is provided wherein the plant partscomprises one or more leaves.

In one embodiment, a system is provided, the system comprising acontroller and a plant photosynthesis characterization apparatus incommunication with the controller, wherein the apparatus comprises oneor more sensors configured to capture a plurality of images of one ormore plants; and a computerized system coupled to receive the one ormore images of said plants from the one or more sensors, thecomputerized system operable to generate a three-dimensional modelcomprising the plant parts of said plants from the received plurality ofimages, to measure fluorescence of the plant parts of said plants, andto derive a characteristic of photosynthesis of said plants using themeasured fluorescence of the plant parts of said plants and thethree-dimensional model comprising the plant parts of said plants.

Although specific embodiments have been illustrated and describedherein, any arrangement that achieve the same purpose, structure, orfunction may be substituted for the specific embodiments shown. Thisapplication is intended to cover any adaptations or variations of theembodiments of the invention described herein. These and otherembodiments are within the scope of the following claims and theirequivalents.

1. A method of determining photosynthetic characteristics in one or moreplants, comprising: capturing a plurality of images of plant parts insaid plants with one or more sensors, wherein the plurality of imagescomprises a first image comprising measurement of the fluorescence ofthe plant parts and a second image comprising capture of one or morereflectance images of the plant parts upon exposure to one or morelights; and deriving information regarding a characteristic ofphotosynthesis of the plant parts by multiplying the plurality ofimages.
 2. (canceled)
 3. The method of claim 1, wherein one of theplurality of images is used to determine absorbance by the plant partsin said plant upon exposure to the light.
 4. The method of claim 1,wherein the method further comprises capturing additional images whereinmeasuring and/or environmental conditions for capturing the additionalimages are altered from the measuring and/or environmental conditionsfor capturing the first image and the second image.
 5. The method ofclaim 4, wherein the measuring conditions are selected from location ofsaid sensors, number of said sensors, presence or absence of a filter oneach of said sensors, number of said lights provided, quality of saidlights provided, location(s) of said lights provided, and combinationsthereof.
 6. A method of characterizing photosynthesis in one or moreplants, comprising: capturing a plurality of images of said plants withone or more sensors; generating a three-dimensional model comprisingplant parts of said plants from the plurality of images, wherein thethree-dimensional model comprises one or more geometric parameters;measuring fluorescence of the plant parts; and deriving a characteristicof photosynthesis of the plant parts using the measured fluorescence ofthe plant parts and the three-dimensional model comprising the plantparts.
 7. The method of claim 1, wherein the method further comprisesproviding infrared and/or red light to the plant parts and capturing theinfrared and/or red reflectance images.
 8. The method of claim 1,wherein measuring fluorescence of the plant parts comprises providingred light to the plant parts, removing the provided red light from theplant parts, and measuring the fluorescence of the plant parts promptlyafter removing the provided red light.
 9. The method of claim 1,performed in a chamber, wherein the chamber contains one or moresensors, one or more lights, and one or more environmental controls,wherein the method further comprises using said environmental controlsto control one or more of temperature, humidity, oxygen, carbon dioxide,and wind in the chamber.
 10. The method of claim 1, further comprisingone or more instruments, wherein the method further comprises using saidinstruments to measure time of flight from said instruments to the plantparts.
 11. The method of claim 6, wherein deriving a characteristic ofphotosynthesis of said plants comprises mapping information from themeasured fluorescence of the plant parts onto the three-dimensionalmodel comprising the plant parts.
 12. The method of claim 1, furthercomprising estimating the light absorbed by the plant parts by at leastone of red light and infrared light reflectance images of the plantparts, wherein deriving a characteristic of photosynthesis of saidplants further comprises multiplying the measured fluorescence of theplant parts by the estimated light absorbed by the plant parts.
 13. Themethod of claim 1, wherein deriving a characteristic of photosynthesiscomprises deriving one or more of a rate of photosynthesis, efficiencyof photosynthesis, and linear electron flow (LEF) within the plantparts.
 14. The method of claim 1, wherein the one or more sensorscomprise one or more cameras and the one or more cameras comprise one ormore filters mounted on said cameras.
 15. The method of claim 1, whereinthe plant parts comprise one or more leaves.
 16. A plant photosynthesischaracterization apparatus, comprising: one or more sensors configuredto capture a plurality of images of one or more plants; and acomputerized system coupled to receive the plurality of images of saidplants from said sensors, wherein the computerized system is configuredto generate a three-dimensional model of the plant parts from thereceived plurality of images, to measure fluorescence of the plantparts, and to derive a characteristic of photosynthesis of said plantsusing the measured fluorescence of the plant parts and thethree-dimensional model of the plant parts.
 17. The apparatus of claim16, further comprising one or more lights configured to provide infraredlight, actinic light and/or measurement light to said plants.
 18. Theapparatus of claim 17, further comprising a chamber, such that saidsensors, said lights, and said environmental controls are configured tocontrol one or more of temperature, humidity, oxygen, carbon dioxide,and wind in the chamber.
 19. The apparatus of claim 18, furthercomprising one or more instruments configured to measure time of flightfrom the instrument to the plant parts of said plants.
 20. The apparatusof claim 19, wherein the computerized system is further configured tocompensate for multiple layers of leaves in said plants by deriving acharacteristic of photosynthesis of said plants.
 21. The apparatus ofclaim 19, wherein the computerized system is further configured toestimate the light absorbed by the plant parts by at least one of redlight and infrared light reflectance images of the plant parts, and thecharacteristic of photosynthesis derived comprises a multiple of themeasured fluorescence of the plant parts by with the estimated lightabsorbed by the plant parts.
 22. The apparatus of claim 19, wherein thecharacteristic of photosynthesis derived comprises one or more of a rateof photosynthesis, efficiency of photosynthesis, and linear electronflow (LEF) within the plant parts of said plants.
 23. The apparatus ofclaim 19, wherein said sensors comprise one or more cameras.
 24. Theapparatus of claim 19, wherein said cameras comprise one or more filtersmounted on said cameras.
 25. The apparatus of claim 19, wherein saidplant parts comprises one or more leaves.
 26. A non-transitorymachine-readable medium with instructions stored thereon, theinstructions when executed operable to cause a computerized system to:capture a plurality of images of one or more plants via one or moresensors; generate a three-dimensional model comprising plant parts ofsaid plants from the plurality of images; measure fluorescence of theplant parts; and derive a characteristic of photosynthesis of saidplants using the measured fluorescence of the plant parts and thethree-dimensional model comprising the plant parts.
 27. The medium ofclaim 26, wherein the characteristic of photosynthesis derived comprisesone or more of a rate of photosynthesis, efficiency of photosynthesis,and linear electron flow (LEF) within the plant parts.
 28. The medium ofclaim 26, wherein said sensors comprise one or more cameras and saidcameras have one or more filters mounted thereon.
 29. The medium ofclaim 26, wherein said plant parts comprise one or more leaves.
 30. Asystem comprising: a controller; and a plant photosynthesischaracterization apparatus in communication with the controller, whereinthe apparatus comprises: one or more sensors configured to capture aplurality of images of one or more plants; and a computerized systemcoupled to receive the one or more images of said plants from saidsensors, the computerized system configured to generate athree-dimensional model of the plant parts from the received pluralityof images, to measure fluorescence of the plant parts, and to derive acharacteristic of photosynthesis of said plants using the measuredfluorescence of the plant parts and the three-dimensional modelcomprising the plant parts.